JP4922175B2 - Location-based social networking system and method - Google Patents

Location-based social networking system and method Download PDF

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JP4922175B2
JP4922175B2 JP2007537990A JP2007537990A JP4922175B2 JP 4922175 B2 JP4922175 B2 JP 4922175B2 JP 2007537990 A JP2007537990 A JP 2007537990A JP 2007537990 A JP2007537990 A JP 2007537990A JP 4922175 B2 JP4922175 B2 JP 4922175B2
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users
profile
location
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JP2008517402A (en
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ジェイムズ エス ローゼン
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ヤフー! インコーポレイテッド
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Priority to PCT/US2005/037540 priority patent/WO2006044939A2/en
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/22Tracking the activity of the user
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/953Querying, e.g. by the use of web search engines
    • G06F16/9537Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0241Advertisement
    • G06Q30/0251Targeted advertisement
    • G06Q30/0267Wireless devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0241Advertisement
    • G06Q30/0251Targeted advertisement
    • G06Q30/0269Targeted advertisement based on user profile or attribute
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0241Advertisement
    • G06Q30/0272Period of advertisement exposure
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/06Buying, selling or leasing transactions
    • G06Q30/08Auctions, matching or brokerage
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/01Social networking
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M15/00Arrangements for metering, time-control or time indication ; Metering, charging or billing arrangements for voice wireline or wireless communications, e.g. VoIP
    • H04M15/04Recording calls, or communications in printed, perforated or other permanent form
    • H04M15/06Recording class or number of calling, i.e. A-party or called party, i.e. B-party
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/029Location-based management or tracking services
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/20Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
    • H04W4/21Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel for social networking applications

Abstract

Systems and methods for profile matching and promotion. Location-related data and other profile characteristics are used for promotion and for matching of businesses, venues and other entities with user specified criteria.

Description

  The present invention generally relates to a system and method for generating and collecting profile information about people and entities and matching or filtering the people and entities based on the profile information.

  Social networking systems can use profiles to connect people who want to meet each other. The idea of connecting other people and friends who would not meet in any other way is powerful. However, the value of these systems is based on the basic methods used to perform matching: common work relationships, social relationships, family relationships, compatible physical characteristics, or food, clothing, leisure activities, sports and entertainment. And may be limited by basic preference features such as self-declared preferences for music, art, etc.

  A serious problem with such a basic social networking system is that the matching criteria are lacking in verifiability and authenticity, leading to flooding of poor quality matching. Too many low-quality matches loses the reliability of the entire system, makes it less useful overall, and is a credit problem when meeting people (connected to entities) through such matching criteria Will be invited.

  As another problem, such systems force the user to perform the tedious task of creating a self-generated profile by entering personal information, similar to filling out a questionnaire. This leads to two problems that are inconvenient for the participants and that there is no standard that everyone can trust. First, many people are busy or neglected. Systems that rely on users to create and update multivariate profiles are inherently flawed. Too many people make their profile boring. Second, people have different standards when coming to self-declared information. I think I am a connoisseur of wine and, according to someone's definition, I think I am a beginner. Furthermore, the information you supply yourself when creating your profile may not be useful in distinguishing yourself from other users in the system. For example, you can say you are a Red Sox fan in your self-generated profile. However, this information is not useful to distinguish among thousands of other red sox fans in the Boston area. Something subtle is lost. For example, you want to meet others who are enthusiastic fans and who have season tickets like you. In other words, gradual change information is important and in some cases it can be lost or mischaracterized with a self-generated profile.

  Therefore, there is a need for an improved system and method for adding rationales and standards to a user profile, ideally a system and method that does not burden the user with the cumbersome task of building and maintaining the profile. There is also a need for improved systems and methods for matching and filtering users based on location and context. Further, there is a need for an improved system that not only matches people with other people, but also allows people to be matched with “entities” such as restaurants, bars, organizations, parties, shops, and cities.

  The present invention relates to social networking systems and methods. Using location-related data and other behaviors and exogenously generated characteristics to replace or supplement self-generated profiles and improve the quality and reliability of matching done using the system , Making it easy to enter profile information.

  The novel features of the invention are set forth with particularity in the appended claims. The features and advantages of the present invention will become better understood from the following detailed description and accompanying drawings, which illustrate embodiments using the principles of the present invention.

  Embodiments of the present invention provide systems and methods for collecting and generating profile information for a user of a mobile device and matching users based on those profiles. In particular, the mobile device can generate or receive location-based information to enhance both the generation of profile information and using that information to match users in different situations. In particular, the profiles and how they are used can vary based on the user's location and the programmable filters and settings established by the user. For example, let users in nightclubs on Saturday nights know about nearby friends, or other users with common friends, or other characteristics that direct matching or facilitate social meetings I can inform you. On the other hand, different profile information and filters can be used when the user is at a weekday industrial trade show. The situation can be easily set by the user (by manually selecting “work mode”, “social mode”, etc.) and / or automatically by the device based on time, location and other parameters Can be set to To this end, the device uses some programmable logic to give the user a “social mode” given the statistical information to guess, eg a combination of location, time and other factors. The situation involving the use of statistical information that is the highest is automatically determined, thereby relieving the user from troubles that have to periodically adjust the user device settings.

  Profile information can be generated from user behavior characteristics, exogenously generated characteristics, and user specified information. Further, the profile may include a unique identifier and one or more anonymous or temporary identifiers for privacy purposes. The profile can then be used to suggest matching between users or to give the user an icebreaker (a conversation topic suitable for starting a conversation).

  Data fields in the user profile can be tagged to indicate the type of data (behavior, extrinsic, user specified or other format), as well as the quality of the data for matching purposes. Quality factors may include an indication of the relevance of specific data to the user and the reliability of the accuracy of the information. For example, data may be collected based on the location visited by the user. However, if the location could not be tracked on most days, data on a small set of locations visited by the user may not provide meaningful information about the user's behavior. In addition, the authenticity of the data depends on the source of the data (eg whether it is user-specified or obtained from an exogenous source) or the data has been verified by a trusted source Depends on whether or not. For example, my user profile may indicate that I am a friend with Joe Smith. This information can provide a useful way to match people with common friends. However, Joe may never think I am a friend. Therefore, his friend Bona Feid believes that I am Joe's friend and is misguided to a meeting with me and knows later that Joe hardly knows me. This type of trust problem frequently occurs without some means of qualifying the reliability of the data used for matching. Without other credit instructions in the data, the usefulness of the information cannot be determined and the entire matching system becomes a problem. If the matching system is intended to instill a reliable connection, people feel that they have finally been cheated by trusting the system and can only find that they have been associated with falsehood Can be abused. On the other hand, the credibility of this information (and generally the system) is that Joe confirms, verifies, or evaluates our relationship, or (as an alternative to doing the same) my behavior profile If I indicate that I spent a lot of physical time with Joe (via GPS tracking or other means) or if I communicate regularly with him by phone or email it can. Therefore, supplementing the information presented by the user with action information obtained from the observed action significantly increases the credibility of the data used for matching and thus improves the overall experience of the user. Can do.

  FIG. 1 is a block diagram illustrating a mobile device 100 that can be used in connection with embodiments of the present invention. This mobile device may be, for example, a personal digital assistant (PDA), a cellular phone, a laptop computer, a pager, or other communication device. The exemplary device 100 includes a central processing unit 102, a memory 106, a network interface card (NIC) 110, a global positioning system (GPS) 112, and a bus 104 for communicating between these components. The memory 106 may store profile information 108 that includes profile information about the user of the mobile device 100, target profiles for matching other users, and settings and filters for using these profiles. The memory 106 may also store profiles in a relational database, flat file system, or other database or file format. This storage of information about the device 100 is ad hoc (in-situ) when another device is encountered (eg, via Bluetooth or other communication interface) regardless of whether there is a connection to a particular network or server. Allows matching to occur on a (limited) basis. For example, FIG. 2 shows two mobile devices 202 and 204 using direct communication to exchange selected profile information (e.g., may include a target profile that indicates potential matching). . Either device can determine if there is a match and send notifications to other users.

  The profile information 108 can be used by application software stored in the memory 106 and processed by the CPU 102. All or part of this information may be stored in a separate network server, which may generate, maintain and process user profiles. NIC 110 or other network interface accesses an external network to allow communication with network servers and / or other mobile devices.

  In some embodiments, the user can participate using a passive identifier such as a card in his wallet. If the system can track the user only by physical characteristics of the user with a casino-style camera connected to a computer running facial recognition software, or through other biometric identifiers, the user In fact, you can join without doing anything or nothing, ie the user's profile is updated and retrieved as needed by the system as the system “watches” the user. The In certain embodiments, the devices and equipment intended to use this system can be replaced with chips and devices that are implanted in people's bodies, biometric identifiers, and other tracking technologies. Thus, embodiments of the invention are not limited to smartphones and other mobile devices, but can be adapted to encompass other technologies that can be implemented.

  The GPS 112 generates profile information and generates location data that can be used to match users. Other position-based information can be generated or received instead of or in addition to the position information generated from the global positioning system. In some embodiments, location information can be generated based on a cellular telephone network (eg, based on the cell where the phone is located, or by more sophisticated triangulation techniques), or a device where location data is available. Alternatively, it can be generated by determining the degree of access to the network access point. In other words, a device without location data can know at least approximately its location if it can communicate directly or indirectly with a device that knows its location (eg, depending on GPS) Devices that are indoors and cannot see the sky can be daisy chained to pass location information from nearby devices that can see the sky). In addition, certain venues may broadcast or otherwise provide information regarding specific locations, events or activities (eg, via Bluetooth, Wi-Fi or other mechanisms). When a user enters or exits a nightclub, amusement park, sports stadium, concert hall or other venue, it sends a message to the mobile communication device indicating its location and other information about the event or activity be able to. Different messages are sent to different parts of the venue so that, for example, the user's device in a multi-screen movie theater can know which movie the user will see. It also uses local triangulation systems or mechanisms to determine the user's relative location to identify specific “micro-locations” or to help users find each other in the venue. This is particularly useful when users do not know each other, for example, when a match occurs between others in a crowded bar (the micro-position method is Including the strength and direction of the signal received between the users, thus acting like a compass, the arrow pointing to the target user and the “hot / cold” instrument indicating the distance). The identity of other users and devices within the specified range is collected and time stamped for use in user profiles that incorporate privacy protection measures (for example, in the name of people near you) There is no meta information recording and time stamp processing). In addition, if other users and devices include location information (eg, GPS location, location entered by the user, etc.), this information may be included in the profile even if the user's device cannot generate this information. It can also be associated.

  Data about people in the same venue can be used to improve the user's profile. For example, if a user goes to a bar with people in their 20s and 30s who are working in the financial sector, this can be used to “teach” the system about users who can be notified of matching options. Similarly, information known about people visiting a given location can be used to build a profile of the location itself, so a bar can be used at a day time or at Fenway Park. Based on whether there is a game on that day, an “entity profile” can be developed as a hangout for motorcycle enthusiasts, red sox fans, or both. If an entity has profile information associated with it, anyone who wants to go to that bar can access this information in advance. A profile matching algorithm can be used to predict whether you will fit the bar patron. Behavior information (eg, whether the user frequently goes to a particular bar or a particular “type” bar) and / or user declaration information (eg, when the user clearly evaluates the experience at a given location) The feedback system used can be used. Entity profiles and their customer profiles can interact dynamically, build together, and evolve in a guaranteed manner over time.

  This process of selecting places to spend time, such as bars, nightclubs, schools, restaurants, country clubs, vacation resorts and companies (you may be hired), etc., is what happens today without assistance from technology That is, people go there if they like the place. Alternatively, people go to the place based on recommendations from friends. Embodiments of the present invention serve to introduce statistical analysis elements into human processes that are characterized by inefficiency and trial and error while at the same time removing some time and effort. This is not intended to exclude the unexpected nature of human discovery or trumptive subjective recommendations, but rather is intended to be useful as a supplemental guide system.

  FIG. 3 is a diagram illustrating a network 300 according to an embodiment of the present invention. The network 300 includes a network server 302 and a database storage system 304. Database storage system 304 stores profile information about the users of the system. Database storage system 304 may store profiles in a relational database, flat file system, or other database or file format. Network server 302 collects information from mobile devices and other sources and generates profile information. For example, the network server 302 may collect information regarding the use of an email account to communicate with other users of the system. The network server 302 also collects information about the user's location and processes the profile to match the user based on this information. Some or all of this information can be stored on individual devices to allow ad hoc matching, but by using a network server, information about the venue can be collected whether or not a particular user is at that location. Allowed to do. For example, the server can determine the number of users at a particular nightclub, the number of potentially matching users, or whether a particular friend is at the location. Some users may request this information in advance to determine if they should go to a particular location. It may also be aggregated (or individually) for the purpose of evaluating advertising opportunities at a particular venue (eg, determining whether advertisements should be displayed on a monitor at that event based on the user's profile at a sporting event), or for other purposes. Profile information can also be provided. The network server 302 can also be used to collect background information about the venue and the people going there. Such information is useful for people interested in knowing patterns such as who goes to the venue frequently and when. The user may want to know, for example, whether people with common friends tend to go to a given club frequently. Similarly, if you plan an incorrect meeting, you want to know who you know is not currently at the venue, or who are legitimate or possibly appear there (the likelihood is statistical Analysis and cross matching between acquaintance profiles and entity profiles).

  In the illustrated embodiment, the server 302 is connected to the Internet 306 for communicating with other devices. In other embodiments, the server can be directly connected to a wireless network, a cellular telephone system, or other network. In the illustrated embodiment, mobile devices 310, 314, 316, 324, 326 and 328 connect to the Internet (or other network) in various ways to allow communication with server 302 and other mobile devices. can do. For example, the device 310 can be synchronized with a personal computer 308 that provides a connection to the Internet. Data can be exchanged with the server via the personal computer 308. Further, data for the user profile can be entered through the personal computer 308 regardless of whether the personal computer 308 is connected to a particular mobile device. Similarly, data for a user profile may be sent from a (networked) device (330, 332), eg, a DVR, smart card, digital book reader, etc. The mobile devices 314 and 316 may also be connected to the network via a wireless server 312 that provides connection to the Internet. For example, wireless “hot spots” are increasingly being provided in coffee shops, libraries, and other locations, and may be provided at night clubs, sporting event venues, or other venues visited by users of the system. Mobile devices 324, 326, and 328 may also be connected to server 302 via a cellular telephone network. Mobile telecommunications switching offices 320 and 322 may communicate with mobile devices 324, 326, and 328 using cellular telecommunications protocols (eg, CDMA, GSM, TDMA, or other protocols). Mobile telecommunications switching offices 320 and 322 can then connect to the Internet 306 through local office 318.

  FIG. 4 is a block diagram of a user profile 400 according to an embodiment of the present invention. Although FIG. 4 shows a data structure for an exemplary user profile, it should be understood that other databases, data structures and formats can be used to store and associate desired data with a user profile. The mobile device 100 and / or the network server 302 can be used to generate and update the user profile 400. User profiles may also be imported from other systems.

  The example user profile 400 can be stored in a relational database and can have an association table for storing profile data 402 and settings 416. Data table 402 may include entries for various characteristics to be stored as part of the profile. Each characteristic may be stored as a row in the data table 402. Data table 402 may include an entry, user type 450, indicating whether the profile is for an individual or an entity (eg, a restaurant, entertainment venue, etc.). For example, an entry may include a field identifier 404 to identify the entry, a data value 406, a data type 408, quality indicators such as relevance 410 and trustworthiness 412, and application settings 414 in the settings table 416. A pointer or other link may be included. Settings table 416 includes settings and parameters that control how entries in data table 402 are used for matching and other purposes. The settings table 416 includes user settings 418 and default and automatic settings 426 established by the system (eg, mobile device 100 or network server 302 application software). The user controls the availability 420 of the data entry for various uses, whether the data entry is used alone or must be aggregated 422 with other specific information prior to use, and other privacy settings 424. You may give the setting to do. Default settings for each of these options may be established and stored in table 426. Further, the automatic settings may be stored in the table 426 by the system for options that cannot be changed by the user.

  Hereinafter, an example of the data table 402 and the format of entries that can be stored in this table will be described in detail. The data entry includes a format 408 that indicates how the data was collected or generated. The format of the data may include behavioral characteristics collected by the system based on user behavior, extrinsic information collected from sources other than the user, and information provided by the user. Data entry also includes an indication of the quality and usefulness of the information. In the example shown in FIG. 4, relevance 410 and credibility 412 may be associated with data stored in a table. Relevance 410 and credibility 412 can be indicated with a numerical rating based on how the information was collected, generated and / or confirmed. For example, the relevance 410 may indicate whether behavioral characteristics or composite data were generated from a large sample size. For example, if the data entry is based on the user's location, it cannot be generated unless the user's location can be tracked (this can be controlled by device settings 416 or positioning). May be limited by the scope and availability of the system). If the user's location is tracked extensively, this data entry may have a greater relevance as an indicator of the user's behavior. For example, a match may be taken between two people who drink coffee every morning at the same coffee shop. This information can at least be used to work as an ice breaker. A trustworthiness 412 can also be indicated. Information that has been validated or rated by additional sources against data entry generated from actions tracked by the system, data given in the form of secure tokens, or user-declared data, with a high level of trustworthiness Can be associated with

  The use of behavior and exogenous occurrence information in the user profile can significantly improve the quality of matching and the type of matching that can be performed by the system. The following illustrates behavior and extrinsic occurrence characteristics that can be used to enhance a position dependent matching engine included as part of server 302 and / or mobile device application software in accordance with embodiments of the present invention.

Phone and email usage : Rather than relying on a flat contact list or requiring the user to classify everyone in the contact list, the network server 302 or mobile device 100 can Monitor SMS and / or email usage (and / or other communication devices, or accounts or connected devices including PCs) to find out who the user actually knows and the nature of the relationship (work / Information about social) can be inferred, i.e. a system that collects all of this in an automated form is richer than a system that always requires manual input. If I talk to John Barnes for an hour every day, I can guess I know him very well. As a result, I wanted to know if John Burns was accidentally in the shopping street I entered (or vice versa), while on the contact list but once for 5 minutes a few years ago Not always careful to meet someone who has just spoken. (Alternatively, there may be situations where the user wants a looser and more remote connection, because they tend to be more than intimate and far away from the user's network. This is particularly useful when looking for a job, a person who is likely to become a sales customer, etc. In the sense of business, The theory is that distant contacts are actually more valuable than a small group of very intimate contacts.) This actual usage information, when used for matching, is more than a flat contact list It is abundant. This also adds some mutual benefit, i.e., I can't claim that she is a friend, even if Gwenes Paltrow somehow appears in my contact list. I have never talked to her on the phone. Mutual benefit and authenticity are important factors for second grade matching (ie, two people are connected via mutual acquaintances). Because if you try to leverage the instantaneous reliability that arises when two other people know you know someone in common, you can connect people through sincere mediation Because it is important. It is worth noting that behavior information can be combined with user input information for greater abundance. For example, when a user is talking to someone on the phone, a record of such a conversation is automatically logged. This record can then be enriched with comments from users annotating or rating the conversation and the contact.

  This data can be entered into the user profile 400 by the network server 302 or the mobile device 100 (or a mobile device connected to a PC). For example, mobile device 100 may be a cellular phone that has a contact list in memory 106. The cellular phone can track the frequency of calls to each individual in the contact list and the amount of time spent on the call. In addition, frequently dialed numbers (or numbers of people who call you frequently) can be automatically added to your contact list, even if no other contact information is available, the phone number in the data Can be associated. A laptop computer or mobile email device (which can be the same device as the cellular phone or a different device) can track the number of messages sent and received from various email addresses. This information can be tracked separately or can be associated with a contact list. Network server 302 and database storage system 304 can allow multiple mobile (or non-mobile) devices to be registered with the same user profile. In this way, both email usage and telephone usage can be associated with a particular individual in the user contact list. The contact (or specific email address or telephone number) with which the communication is to be performed may be added as an entry to the data table 402 of the user profile. For example, field 404 may be added for a contact such as “John Barnes” (which may be linked to other contact information for the individual via a relational database). The value 406 may be a number representing the frequency and duration of communication. Format 408 is classified as an action. The relevance 410 may be a numerical value based on whether the sample size is large (how long tracking is turned on and how long) and whether both email and phone accounts are registered with the system for tracking. The credibility 412 determines whether the communication is combined with all contact records (or email address or phone number only), whether John Barnes is also a registered user, he identifies the user as a friend, and / or Or a numerical value indicating whether his contact information or communication usage information matches the information in a particular user profile, whether there is a physical accessibility history, or other factors indicating the reliability of the data .

Physical accessibility : Similar to normal telephone conversations between people, physical accessibility can dictate the relationship and its degree of intimacy. For example, a Bluetooth enabled mobile device can automatically log the time that two (or more) people spend with each other and can be used to “authenticate” the relationship. This includes a “time shift” proximity that indicates that two people are in the same location but not at the same time, and this is also supplemental information useful for establishing a relationship (eg, they Live in the same dormitory, even if not always at the same time, or go to the same library regularly). Physical accessibility can be used as a separate data entry or can be combined with the use of phone and email to substitute for the level of relationship (whether you are a registered user of the system) with others. You can also generate an overall data value to use as.

Where you go : In addition, the location that the user visits can be used to match or improve the credibility of other data entries. A field 404 may be added for frequently visited locations. The value 406 may be the coordinates of the location where the user has spent significant time. This data is separated by the date and time when these locations were visited, so that locations visited during work hours can be distinguished from locations visited on weekends or at night. The venue also has wireless capabilities, and can provide tags or tokens with additional information about places visited (concert halls, amusement parks, sporting events, etc. when a particular artist plays). In addition to using this information to match, give this to the user as a potential ice breaker for conversation, for example, and let them know that both are fans of Elvis Costello (Because both sides saw him at the concert), this is something we want to discuss as a way to “breaking the ice”. If the data is digitally signed or otherwise made difficult to spoof, it must be added that a token can be used to validate the data.

  “Where are you going” information can also be used by advertisers and other companies who want to know more about you for marketing purposes. For example, a token indicating that you have watched the same movie many times is useful not only for matching purposes (notifying other similar hardcore fans about your interests), but also for advertisers. Spider-Man marketers want to hype their sequel by sending special messages or promotions only to those who can prove that they have seen the first movie at least three times (in a cinema). This is made carefully as follows.

  The data can also be used to improve the relevance 410 and reliability 412 of other data entries. For example, if I go to see Red Sox games 81 times a year, it is appropriate to put more weight on my interest in Red Sox than in the case of self-generated profiles. Also, this information does not require manual entry by the user. This can be recorded automatically as long as the game goes to Fenway Park on a certain day (use a location tracking device or have my matching device send a transmitter or mail in Fenway Park). By "informing" where I am by interacting with a mating device or other network device in the event). Unlike self-generated features that are subjective, my location facts are objective and verifiable and can specify a high value for the trustworthiness 412 in the data table 402. (Spoofing can be assumed to be a problem because these devices and location-based matching systems are prevalent and threaten the reliability and usefulness of the system. Using an authentication mechanism such as a token with a digital signature, To people or other interested parties (such as advertisers offering special deals to the most enthusiastic fans), you actually instructed you (or your profile) You can “prove” that you were at the site.

Other actions : what coffee stores you go to frequently, what gym you go to (how often), what time you wake up, whether you go to church every Sunday, what TV shows Whether you record (or watch) on a digital video recorder (DVR), what website you visit (and what you buy, what cookies you have on your computer, otherwise , What to do online), and in that regard, any action using a trackable device or device or trackable action is all talking about who you are. Thus they can also improve the matching and supplement or trump card of what you say about yourself in the profile, ie they occur automatically (passively from the user's point of view) It is easy to “enter”. These factors can be tracked based on the location / movement of the device and can be tracked by the network server 302 or other devices and systems (directly or indirectly) connected to the mobile device (eg, recording). DVR service that tracks TV shows that have been viewed and watched, or a cellular telephone network that tracks phone usage). Since these types of activities are technically easy to obtain, it may be desirable to stop monitoring these activities to avoid confusion and to simply protect the user's privacy.

Feedback system : The feedback system can also be used to provide information to the user profile 400 for generating data entries. What happens when people have the ability to "tag" you with feedback? Does your previous girlfriend look down on you? If you have an exogenously generated rating on you in your profile that you cannot edit, it will help others rate you. As a result, you do not want people to downgrade your “personal credit rating” and thus lead to “good” behavior. Thus, this is similar to an EBay feedback rating that is useful for notifying others about whether someone can be trusted. It is also an interesting way to “collect” and show “friendly action points”. There is also a powerful karmic ingredient to build and maintain an active interpersonal rating. These data entries have a different format 408 than the behavior data entries described above that are tracked by the system. These entries can generally be tagged as extrinsic data, or more particularly as feedback from another user. The value 406 can be a rating in various categories and can also include specific comments (visible to others based on the nature of the comment, who is seeking access, and other rules that can be applied to this powerful information. Or not visible). The relevance 410 may be based on the amount of feedback received, and the credibility 412 may include the individual giving the feedback (whether the individual itself has a positive feedback rating?) And its (by location or communication tracking) It may depend on whether the relationship with the individual can be verified.

Secure tokens : Restaurants, bars, clubs, communities, churches, universities, and other venues and associations can provide authentication (digitally signed) “tokens” that can be added to a user's profile. These tokens may generate new data entries 402 or may be used to increase the reliability 412 of existing data entries. This was whether people were “true”, that is, really a member of the club, really belonging to the gym, really a graduate of Vilanova, or really an honorary discharge from the military Make sure that you are a frequent aviator of Delta Platinum Medallion. This is useful in matching situations: when a woman is in a bar and meeting with a fellow alumni, she says she is a graduate of her alma mater and spent time there but did not graduate It is important to make sure that you are a real graduate, not an expert.

People you know : The contact list is a useful means of matching users, ie using a common acquaintance as an intermediary is a powerful way to match users. A frequent problem is that the contact list is only a fraction of all of your actual acquaintances. In order to maximize the effectiveness of the contact list as a matching method, entries (of people you know) should be generated based on the normal contact list and observed behavior as described above Can do. These entries can also be entered manually by the user, and can include behavioral characteristics (as described above) or extrinsic information, eg, manual feedback from an acquaintance who knows the relationship (and its level of intimacy), Trust 412 may be increased (or decreased) due to the presence of corresponding inputs in the user profile. As described in more detail below, matching or alerting can occur when a friend is nearby (based on location data and user profile), or an individual with one or more common friends is nearby (or actually close). Or if you have common friends). For example, the system would like to alert you that a good friend of your best friend is about to walk past the coffee shop you are eating.

  Extending this theme can enrich your profile with other information. Some examples: purchases you make (online or offline) with digital cash or credit card; transaction details can be integrated into your profile. EBay feedback ratings can be attached to your profile and used "beyond EBay" (people only meet people or hire people or do business with people with high EBay feedback ratings) You may wish). What dating sites you belong to (and information about those sites) can be shared with your profile. The advertisements you see (online or offline) and the advertisements that you respond in some way are valuable to market traders who want to sell things to you. More generally, integrate your credit rating, police record, medical record, driving record, grade and work performance rating, and other “scores” from various real life activities into your profile, It can be helpful for matching or other purposes. (In some cases, you can use a digital token for verification.) Using this information in your profile means that someone will meet you, hire you, give you credit, and make you special Including whether or not you wish to offer unique promotions or show you advertisements (either online or offline in the case of dynamically targeted advertising methods such as challenging billboards) Good.

  All this information is powerful to help people learn and trust quickly about others. This is also valuable for business because past purchase behavior is a powerful clue to future purchases. Some of the technologies developed online are, for example, offering dentist advertisements to individuals who have just searched “Chicago Dentists” on Google. In this case, what users search online, what to buy with a credit card or digital cash in a shopping street near home, what movies to watch, what restaurants to eat, what TV programs to record and By combining a rich array of behavioral data such as viewing or / or viewing, there is a very powerful opportunity for marketers to make a one-to-one match between people and their products. While we propose a way to connect people, matching between people and “lifeless entities”, eg companies, is also an important element of the present invention. Systems that collect and process behavioral data, including location data, are of a transactional nature and have the ability to appeal to users and send alerts to help the business. As an example, a store will seduce you when you enter a competitor's store, sending you an alert and possibly offering you a discount. Another example is to dynamically change the billboard based on who views the billboard (and what they know about the user based on the user's profile). Yet another example is determining that patterns that are useful to marketers, such as those who see Red Sox games, tend to eat Dunkin Donuts twice as often as those who do not. In this way, it can be used to better determine the success (measured as a return on capital) for an advertising campaign. For example, what percentage (as determined by location tracking data) of those who saw a Great Adventure billboard along a particular highway visits within 6 months. The granularity of behavioral information described here is much larger than anything that has been achieved in the past. Many people do not want their behavior monitored, movements tracked, synthesized into a profile and shared with advertisers, but this information meets friends or matches the target profile You may want to be tracked for some of the social benefits described here, such as setting up meetings with others. When this data is collected for one purpose, people can find that there is a motivation to selectively share it with market trading companies. Just as a gambling person shares behavioral information with a casino to earn additional income, and a traveler shares flight history with an airline to qualify for free flights and priority handling, People spend $ 1000 on Prada, so when they enter the shopping street, every second women's fashion store sends an “alert” and offers a special discount on what comes to that store. Can be acknowledged. Broadly speaking, the motivation for sharing personal information with marketers is cash payments, well-targeted advertising messages about people's interests, and special offers from companies that are easy to get trades. And free or subsidized devices for interacting with matching systems, etc., or service fees.

  Of course, the user can determine how to share their information or whether they wish to share information. In some cases, the user may wish to share a private medical record to indicate that he has recently been diagnosed but has no sexually transmitted disease (to authenticate this information). , Signed and date stamped tokens can be issued by a doctor or clinic). In this case, they may specify that only a portion of their medical records can be shared only in a very specific environment. Suppose there may be a set of rules that give the user the authority to control this information as needed. A simple aspect of how these rules are applied is described below. It should be understood that these rules have been simplified for practical purposes here and the system can be improved with more and / or different user controls.

  Clearly, a healthy and rich data set that can be tracked and collected to form a user profile raises privacy issues. A settings table 416 is provided to manage the use of data in the user profile. Each entry in this table can specify a number of settings and parameters to apply to the data entry or data collection. An entry in table 416 can be associated with one or more data entries in data table 402. For example, user settings 418 can be entered by a user through a mobile device or a personal computer. The user can specify a setting for usability 420 that indicates whether it is the type of data or class that must be collected or made available for matching purposes. For example, the user can specify that location data be collected and used based on a specific type of event (night club, sporting event, concert, etc.), but track other locations such as adult night clubs. Or do not use. The user may also specify that location data can be used to match another user only if certain conditions are met (eg, you are within 100 feet of another member of your local Rotary club). Use location-based data to alert you when you are in and within 10 feet of a member of a different Rotary club branch). Similarly, rules may be established to give a photo, email address or phone number to another user, for example, a rule requesting the interchange of photos. The user may also specify certain times, days, or other conditions that limit matching and notification (eg, allow matching only on Friday and Saturday nights). The user may also specify that the level of set 422 should be used for matching based on specific data entries. For example, the user may not want others to be able to match based only on the income level entered in the user profile. However, if the matching is based on a large amount of aggregate data or based on a certain type of reliable data, the user is allowed to include income in an abstract or aggregate form for use by the matching engine. May be (but not allowed to give to other users). Other privacy settings 424 may also be used to limit data collection or use, delete it after a period of time, or limit its use to matching or disclosure to other users. Just as it is easy for a user to monitor his actions, it should be easy to deactivate a record of actions as needed.

  User profile 400 may also include default and automatic settings. For example, the table 426 may specify that the behavior data format cannot be edited by the user but can be deleted. Similar to EBay's feedback rating, the user can reset all feedback from other users, but feedback comments that he dislikes may not be easily editable. Similarly, it may be desirable to have the system use an environmental filter. For example, if you are in a place where you get a large number of matches, the device you use (or the server connected to it) will have a filter that sends alerts only for high quality matches. Can be applied. Similarly, if you are traveling and you do not get a “hit”, the service can use location detection to confirm that you are in a foreign country, or during a given time period. You may simply lower that threshold by simply verifying that you have little (or no) matching.

  In the illustrated embodiment, the user can select one or more target profiles (eg, single women in their 20s with some other characteristics) to determine if there are matching users with a particular profile. May be specified. In particular, the target profile can be used to identify other users who have matching characteristics and are within a certain distance of the user or at another specified location. FIG. 5 is a logic diagram of a target profile 500 according to an embodiment of the present invention. Although FIG. 5 shows the data structure and field format for an exemplary target profile, other databases, data structures and formats may be used to store and associate desired data in the target profile. I want you to understand. Mobile device 100 and / or network server 302 may store one or more target profiles 500 for matching purposes. The target user profile may also be imported from other systems such as an online dating service.

  In order to facilitate manually generated target profiles, the system uses global `` matchmaking intelligence '' by observing and learning from successes and failures among those looking for opponents. Can be developed. For example, the system “sees” the pattern that people who get up early in the morning and walk with dogs tend to get along with other people who do the same thing, so using this behavioral information, you You can find "your computer generated target profile" that is different from the one you choose for yourself. Computers do not necessarily evaluate how people “get along” with each other, but for example, when a person marries and communicates the fact as feedback to the system, this information is provided by direct user feedback. Can be collected. A successful match can also be inferred, for example, by observing that two people who met in January have spent a great deal of time since tracking through location-based tracking. There is a wealth of data (exogenous, self-generated, behavioral, etc.) that can be collected and analyzed, and the computer's increased computing power is combined with Bayesian algorithms, neural networks and other artificial intelligence methods to create a computer Is good for people to improve their “human” skills.

  The example target profile 500 can be stored in a relational database and can have an associated table for storing target data ranges 502 and programmable filters 518. Data range table 502 may include a plurality of entries for characteristics for use by the system to determine whether another user matches the target profile. In the case of a match, an action can be taken based on the setting 416 (eg, beeping, sending a notification, or displaying information about a matching user or group of users). Each target characteristic can be stored as a row in the data range table 502. The entries correspond to those used in the data table 402 (field 504, value range 506, format 508, relevance 510 and credibility 512), but using threshold values, ranges or wildcard values, the user A request can be specified for the profile to match the target profile. In addition, a weight 514 may be assigned to the entry to indicate the importance of the entry in determining whether to match. (Note that the same can be done on an ad hoc basis between two devices in a manner that does not require a centralized database.)

  Other filters 516 can also be applied to entries for matching purposes. The pointer may link or otherwise associate one or more entries in the data range table 502 with the programmable filter 518. Programmable filter 518 can generally specify other conditions for matching or for matching a particular entry. For example, the filter can specify whether a particular entry must be matched and / or whether only a certain percentage of entries need be matched. The filter may be based on location 520, time 522, situation 524, relevance 526, or other condition 528. Location 520 can be used to filter users who are within a certain distance of the user (eg, within a Bluetooth range or based on specific location data), or at a specific location, or a specific event or venue. The location 520 can also be used to automatically adjust the matching rules (eg, when the user is away from home). For example, if the user is traveling abroad, the rule only requires matching with another user who speaks the same language (or came from the same country). The user may also have a setting 416 that indicates the status 524 (eg, whether the user is at work, at home, has a social event, or is traveling). Based on this situation 524, different target profile (s) can be selected and used for matching. Further, the criteria for matching can be automatically switched based on the situation 524 (eg, the user can be informed of a friend who is in the vicinity when traveling, but not at work). The matching criteria can also be automatically adjusted using time 522 (eg, using a different standard than Monday morning on Friday or Saturday nights).

  This system generates "intelligence" by looking for other users' rules and settings at a given time and / or location, and rescues users from having to manually adjust their settings Environmental factors can be “calculated”. For example, the system can distinguish between a bar and a doctor's office by a “location memory”. If some users “map out” a location by identifying the characteristics of a particular location (or, in the case of a multi-use facility), this information Can be applied to other users visiting the location. In this case, the user can simply set his device to “turn off matching at the doctor's office” or “turn off matching everywhere except the bar” and the system will You can respond accordingly.

  Similarly, the system can learn through feedback, i.e., repeatedly snooze certain alerts, and thus indicate that this "seed" alert is not appreciated (based on time, location or other factors). . Alternatively, upon obtaining a matching alert, the user provides feedback to the system through the user interface of his device and sends “please like this, please”. More specifically, the system must be able to train to know where the home is, the workplace, the girlfriend's apartment, etc., so the system learns about you and your behavior patterns Can "understand"

  The relevance 526 is about who you are with (eg, your wife or your mistress) and / or who is with you (eg, a more generous match for people with or near your common friends) and / Or can be used to change matching rules based on who you are connected to (eg, whether you have a common friend with a high level of relevance and credibility). The use of second grade contacts for matching is both a criterion in the data range table 502 and a filter to determine how other criteria are applied. These entries and filters can be used to notify the user when an intimate second grade contact is within a certain range or distance (eg, based on a location 570 filter). Also, the venue or event can be scanned (by making a request to the network server 302) to determine how many friends and / or second grade contacts are at that location. Furthermore, if the user's calendar information is incorporated into this profile, this information can be used to predict who is at a particular location in the future. For example, if you are planning to go to Miami on the weekend, you will not only scan the city to see who is currently there, but also someone (your acquaintance or You can also check that you have a plan to go there. In this way, you can “match” to a suitable blind date with someone flying to Miami from a different city.

  The user can also make a specific request to “scan” an individual (eg, a woman at the end of a bar) with a mobile device at a specific location to see if others have a common friend, or You can simply check her public profile. The network server can retrieve the user profile for the mobile device at a specified location, or it can be obtained through a direct Bluetooth or infrared connection with the mobile device. This is particularly powerful when combined with qualitative indicia for matching information (such as relevance 410 and trust 412). This is because it promotes second grade matching of quality and filters out spoofers. The scanning process can also identify the topic of an “ice breaker” conversation so as to make it easier to start a conversation between others, as further described below.

  You can also use filters to prevent certain matches. For example, suppose you are married but want to send a “digital vibes” that opens up to a discreet romantic approach. In this case, you use the matching engine to alert you to a second grade connection where the intermediary is your spouse and avoid it. You can also selectively block "Vibes" from being sent to your spouse's friend, or send them anonymously only to those who have expressed similar wishes. This can be specified by using a filter based on relevance 526 to change the availability 420 setting for the mobile device.

  In line with the same policy, this may apply to people who are not necessarily married, but simply want an anonymous physical encounter and thus want to be alerted about other people with similar interests. it can. People seeking such things can include this preference in their profiles and the system can incorporate this into its matching criteria. Those seeking this type of physical encounter simply go somewhere, where she does not have to physically approach someone with similar hope (this is today, In fact, you can decide where to go tonight based on where many people with similar preferences gather. She can do this by scanning bars, neighborhoods, and cities before leaving home. This “one-night stand” matching system can be made more effective by combining it with the other profile data described above. For example, someone may be interested in standing overnight, but only someone who spends most of his time outside of her town or neighborhood and has a clean health record regarding sexually transmitted diseases (for someone, , Perhaps motivating to merge medical data into his profile using a digital token issued by his doctor).

  Mobile devices can also be used by companies, and specific filters can be established for these purposes. The company uses myriad uses for real profile data. If you know you will make a million dollars a year when you enter a Prada retail store, or you know that you will spend $ 1000 a month at a competitor store (for example, Because information is communicated and collected from your smart card usage, you are treated more kindly than those who do not know your purchase history. Similarly, if you are walking on an industrial trade show floor and your profile has other desirable characteristics such as work and past performance assessments or electrical engineering grades from a school, hire you There may be an approach by the company seeking to do so (especially if you are instructing your profile to be open to such an offer).

  In some situations, the transfer of authenticated behavioral information is beneficial for both the company and the consumer. In the example described above, for example, a consumer in Prada would benefit from receiving VIP treatment based on her proven purchase history and possibly obtaining a special offer.

  In addition, consumers can be authorized by exogenous data about the business. The restaurant can passively accumulate profile information regarding its “behavior” so that the consumer is considered a person who is likely to become a customer based on past purchase behavior. In this case, the restaurant is an “entity” similar to a human user of the system. Each time someone eats at a restaurant, the mobile device facilitates the rating of that restaurant, for example when you pay an account (perhaps with digital cash or credit card), you enter a rating of 1-10 To be qualified. Your rating is digitally associated with this restaurant in the user profile 400 for the restaurant (similar to the previous girlfriend rating you). The next person who enters (or walks by) the restaurant can see these ratings. This information can be stored in the database storage system 304 or can be stored in a fraud prevention device located locally at or near the restaurant (because of fraud prevention, the restaurant removes negative ratings) Cannot be edited or edited).

  A number of key elements distinguish this from Zagat style restaurant reviews. First, it is specified that it is easy to rate a restaurant while you are at the restaurant and the experience is new to your memory. Second, users can get high-quality ratings when they need it, when they are hungry, walking on the road, and looking for places to eat from their portable devices (of course, the user , You can access the same information at other times and places). Establish a target profile between the user and the restaurant, just as a person is matched with others, and the rating that helps the mobile device inform the user of a good restaurant match and guide the user's judgment Can be given.

  Another application that qualifies consumers is to use composite ratings. For example, Fenway Park can compile aggregates and anonymous information about who goes to the game. In this case, those who want to go to the Red Sox game can find out what kind of people come to the game. This composite information is useful when selecting a bar, ie composite statistical information such as its audience, age, gender ratio, income, local to tourist ratio, etc. (all of which are users in the bar Based on data entry 402 of profile 400). Some are interested in knowing what the crowd's complex state is now like Friday night vs. Sunday night, or just generally.

  The group information need not be only collective and anonymous. "Scan" the bar and use it, for example, to see if someone you know (or second grade contact, a woman looking for an overnight stay, a friend from work, etc.) is in it can. One important benefit is the ability to do this at a remote location (e.g., server 302) while you are still at work or thinking about where to go before you actually go to the bar. By sending an inquiry request). People also have remote composite data about people living in the city they want to move (or their neighbors), companies they want to work, golf clubs they want to join, resorts they want to visit, etc. It turns out to be useful to obtain.

  Embodiments of the present invention also allow for various additional applications.

Contest : It will be fun if you compete with friends to see more acquaintances. In a location-aware matching system, you don't have to “see” people themselves, and the matching engine tells you when you have friends within a certain distance. The authenticity test described here can improve the contest (you probably remove work-related acquaintances from the game or, for example, only “intimate friends” based on a credit rating of 412 Can be prescribed to count).

Karma points : When two people meet using you as an intermediary, you can earn digital karma points (scores or tokens in the user profile 400). Karma points are fun to collect and can also provide a basis for matching (eg, filtering users who are good matchmakers or have multiple second-class contacts). Lifeless entities such as nearby coffee shops that are “responsible” for a certain number of matches (ie, people who are regulars of that coffee point are matched) can also earn karma points. When two people meet using you as an intermediary, you can alert you that it was done and that you just earned 10 “karma points”.

"Ringing Ears" : In addition to earning karma points, when two people meet using you as an intermediary, you will be notified (by phone, text message, etc.) The user can then be invited to participate in the conversation remotely or to participate in. The setting 416 of the mobile device 100 allows the device to call the mediator when matching is done among common friends. Or send a text message or email In addition, the settings 416 may be used to cause the server 302 to send a message to the intermediary.

Riddles and Games : Settings and filters allow you to use creative dialog matching criteria. As mentioned above, people have a public profile that can be shown to some or all of other users. This profile can be accessed through a “scanning” action, which means that someone can “point” his device to an individual (or her device) and access her public profile. In the public profile, by answering a riddle when a man approaches her, or singing her favorite song, buying her a Margarita, handing her some flowers, and so on Hope women enjoy. This can be entertained for both parties to relax. These preferences for the approach are to find a suitable topic to soothe the seat when someone “scans” her expression, or to search for a “hit” (like a mutual acquaintance) that matches. To be exposed. As a sidepoint, there may be a record that holds it whenever someone is scanned. Women like to know that one night, 18 men have found enough attraction to "scan" her.

Digital Wake : Another setting 416 can be used to request notification when some matching or event occurs. Recently, a target profile and filter is established to match users who were in nearby locations (based on matching against time-stamped location entries in the data table 402). For example, a user is alerted when someone they know (indicated by a data entry in user profile 400) passes the user's location within the last 5 minutes. In this case, he calls his friend, says Hello, and probably arranges to go back and meet up close. Also, the filter at position 520 can be used to relax this criterion for matching based on whether the user is located. For example, if the user is traveling abroad, the user wants to be notified about nearby friends within the last few hours. The user also wants to be notified if there are friends at a location where the user has visited before (eg, a restaurant where the user had lunch one hour ago).

  FIG. 6 is a flowchart illustrating a method for matching users according to an embodiment of the present invention. The software application of the device 100 or server 302 can process the user profile and the target profile to determine whether there is a match and if so, what action to take. Any of the profile information and filters described above may be used, and any of the actions described above may be performed based on information in the user profile and target profile. As shown at 602, location information may be generated or received by the mobile device 100 and processed locally by the device or transmitted to the server 302 for processing. The location information requires a user at a specific location or event, or a user or a user within a certain range of the specific location. As indicated at 604, other users who meet this criterion are detected (via direct communication as shown in FIG. 2 or via server 302). Based on the availability settings 420, the device or server then determines whether a user profile (or at least the entries necessary to match based on the desired target profile and filter) is obtained for the detected user. . If user profiles are obtained, they are searched and a filter is applied to the user profile and target profile as shown at 608. As shown at 610, the user profile is then compared to the filtered target profile to determine if it matches. If there is a match, check settings 614 to determine appropriate notifications, alerts and other actions to be taken. Appropriate notifications, alerts, and other actions are then performed by the mobile device 100 and server 302 as indicated at 616. As described above, these actions include notifying the matching user, notifying the matching target, and / or notifying the mediator where the two second grade contacts match.

  As described above, the programmable filter 518 must satisfy individual criteria / entries or meet a certain percentage of criteria / entries for the overall match between criteria and user profile. You can specify whether or not In the illustrated embodiment, ordinary expressions or other logic may be used as part of the programmable filters and / or criteria. A score may be calculated to determine if the threshold is satisfied for the overall match and whether the user should be notified of other users and user profiles that satisfy the threshold. There may be more than one threshold or scale used to determine how to notify the user. If another user with a very high score is nearby, the mobile device emits an audible alert or vibrates and is provided with an SMS text message with information from other user profiles. If the low score that other users have is still high enough for a threshold, a text message is sent without an audible alert. These are merely examples, and other combinations of notifications and thresholds may be used.

  In the illustrated embodiment, a certain criterion is required for matching whether the target is male or female. Other criteria contribute to matching scores that exceed certain thresholds such as income levels. These criteria in some cases contribute zero or a fixed number towards the score (eg, based on weight 514). For example, if the target shares a common second level contact, such as a user or other person listed in the contact list associated with the profile for both the user and the target, a single weight 514 Can be added to the score. In some cases, the criteria allow weight 514 or a portion of weight 514 to be added to the score, with a number of times based on other user profiles. For example, additional points can be added to the score for each common second level contact between the user and the target. A programmable filter 518 can specify a rule that reduces points (eventually to zero) for each additional second level contact in common. The same solution may be used for other criteria, such as adding more points for higher income levels up to a certain maximum value. In another example, a third order contact is used (someone known to each of the user and target can then select a common individual that can be determined based on the contact list or other factors as described above. know). The third contact contributes some points to the score, but contributes fewer points (and has a lower weight) than the second contact. All of the other types of criteria and characteristics described above are based on whether a logical criterion or rule is satisfied, and weights that can be added to the score when that criterion or rule is satisfied (fixed or scaled) Can be factored into a score based on A user interface with dials, slide bars or other adjustable settings can be used to adjust the weights for different criteria, which are the settings that make an important criterion for matching, the weight / points that contribute to the score A setting (or a scale of setting) to specify, a setting that indicates that the criterion is not used for matching, and / or a setting that indicates that the criterion disqualifies the target from matching. The threshold used for matching can also be adjusted by using a dial, slide bar or other adjustable settings. Users can easily toggle dials, slide bars or other settings to increase the threshold score required for matching if there are too many matches or notifications to get at crowded locations. When the user is in a position where matching is difficult to occur (for example, when traveling outside the town or abroad), the user can easily lower the threshold score required for matching. As described above, the threshold can be automatically adjusted based on the situation, time of day, location, or other factors determined by the system.

  Similarly, scores and thresholds can be used for entities such as companies or venues or other objects to determine matching and to determine if the user should be notified. In the illustrated embodiment, similar scores and thresholds can be combined with location-based information to determine whether a promotional item, advertisement, or coupon should be sent to the user. For example, a user may have a credit score, a score based on purchases made, or other criteria that satisfy a threshold. If it is determined that a user with a score higher than the threshold is in the vicinity of the store or company, a specific advertisement or electronic coupon can be sent to the user's mobile device. An expandable threshold may be used such that different advertisements or coupons are sent to the user based on how much the user exceeds the threshold score. In some embodiments, when it is determined that the mobile device is near (or at) the competitor's company, a direction to the company's location, or a company advertisement or coupon can be sent to the user's mobile device . Whether the user is near the location may be based on a preset radius or distance, or may be weighted with different amounts as part of the score based on how close the user is to the location Good.

  While preferred embodiments of the present invention have been illustrated and described, it will be apparent to those skilled in the art that these embodiments are merely exemplary. Numerous changes, modifications and substitutions will be apparent to those skilled in the art without departing from the invention. It will be understood that various modifications to the embodiments of the invention described herein may be used when practicing the invention. The system and method of the present invention shall be limited by the claims and their equivalents.

FIG. 2 is a block diagram of a mobile device that can be used in connection with embodiments of the present invention. FIG. 3 is a block diagram illustrating direct exchange of information between mobile devices according to an embodiment of the present invention. It is a figure which shows the network system based on embodiment of this invention. FIG. 4 is a logic diagram of a user profile according to an embodiment of the present invention. FIG. 4 is a logical diagram of a target profile according to an embodiment of the present invention. 6 is a flowchart illustrating a method for matching users according to an embodiment of the present invention.

Claims (19)

  1. In a network server that manages location-based social networking,
    A data storage component for storing data and instructions;
    The network server executes the instructions,
    Receiving a plurality of profiles, each profile being received for each one of a plurality of users, and each profile associating a plurality of characteristics with each user in the plurality of users;
    Associating a level of credibility with at least some of the characteristics in each profile, wherein the level of credibility in the characteristics is based on a plurality of behavior information associated with each of the users, It is obtained from a source other than each user,
    Associating a level of relevance with at least some of the characteristics of the profile for each user, wherein the level of relevance is a behavior of a sample size at which the at least some characteristics follow a threshold value. whether is determined based on the behavior information obtained from the information is indicative in part,
    Receiving criteria that can be used to match a first user with one of the plurality of users;
    Obtaining information indicating the current position of the first user;
    Determining a match of one of the plurality of users to the criterion based at least in part on the level of trustworthiness, the level of relevance, and the current location of the first user;
    A processor that causes an action including:
    Network server with.
  2.   The network server of claim 1, wherein the at least one characteristic includes information regarding a relationship with another user other than the user associated with the profile, the relationship information being validated by another user.
  3.   The network server of claim 1, wherein characteristics given by each user are associated with a lower level of trustworthiness than characteristics given by other than each user.
  4.   At least one characteristic indicates a relationship between the first user and another user of the plurality of users, and the level of trust is further determined so that the first user and the other user are at the same location. The network server of claim 1, wherein the network server is based in part on the number of times it was
  5. The instructions are provided by the network server,
    Sending a promotional message to the first user based in part on the current location of the first user;
    The network server according to claim 1, wherein the network server is configured to perform an action further comprising:
  6. The instructions are provided by the network server,
    Automatically determines the location the second user has visited, and when the second user is absent, manually specifies the location;
    Using the determined location visited by the second user to further determine a match of one of the plurality of users;
    The network server according to claim 1, wherein the network server is configured to perform an action further comprising:
  7. Accessing a plurality of profiles via a computing device , wherein each profile is received for each one of a plurality of users, and each profile has a plurality of characteristics within a plurality of users. Steps that are associated with each user;
    Associating a level of credibility with at least some of the characteristics of each profile via the computing device , wherein the level of credibility in the characteristics comprises a plurality of actions associated with each user; Information based, wherein the plurality of behavior information is obtained from a source other than each user;
    Associating a level of relevance with at least some of the characteristics in each profile via the computing device , wherein the level of relevance is such that at least some of the characteristics are in accordance with a threshold value. a step whether determined based on the behavior information obtained from the action information of the sample size is to instruct partially,
    Receiving at the computing device a criterion that can be used to match one of the plurality of users;
    Determining the current location of the first user via the computing device ;
    Determining a match of one of the plurality of users to the criterion based at least in part on the level of relevance, the level of trustworthiness, and the current location of the first user via the computing device ; ,
    Providing at least a portion of a profile associated with one of the plurality of users matching to the first user via the computing device ;
    A social networking method based on location.
  8. 8. The method of claim 7, further comprising providing information indicating a match to the matching one of the plurality of users via the computing device .
  9.   The method of claim 7, wherein the at least one profile includes feedback regarding the first user provided by other than the first user.
  10. Determining whether the first user is within a predetermined distance from the merchant using the current location of the first user via the computing device ;
    Sending an advertisement for a competing merchant to the first user if the first user is within a predetermined distance from the merchant via the computing device ;
    The method of claim 7 further comprising:
  11. Determining the current location of other users in the plurality of users via the computing device before;
    Determining whether at least one of the other users is located in a store via the computing device ;
    If at least one of the other users is located in the store via the computing device , at least a portion of the profile associated with the at least one other user is in the store The steps to give
    The method of claim 7 further comprising:
  12.   8. The step of determining the current location of the first user further comprises determining whether at least one event is associated with the current location or whether a merchant is associated with the current location. The method described in 1.
  13. A plurality of mobile devices each configured to perform an action, the action including providing a profile for a user of each mobile device, each profile further comprising a plurality of characteristics associated with each user; A plurality of mobile devices including:
    A network device configured to perform an action, wherein the action receives each profile from the plurality of mobile devices;
    Associating a level of credibility and a level of relevance with at least some characteristics in each profile for each user of the mobile device, wherein the level of credibility among characteristics is a plurality of actions associated with each user. Based on information, wherein the plurality of behavior information is obtained from a source other than each user, and the level of relevance is such that the at least some characteristic is in accordance with a threshold value. or it is determined whether partially indication based on the behavior information obtained from the action information of the sample size,
    Receiving criteria that can be used to match a first user with one of the plurality of users;
    Obtaining information indicating the current location of the first user;
    Determining a match of one of the plurality of users to the criterion based at least in part on the current location of the first user and the level of trustworthiness and the level of relevance;
    Providing the first user with at least a portion of a profile associated with the matching one of the plurality of users for display on the first user's mobile device;
    A network device that includes
    Social networking system based on location with.
  14.   The system of claim 13, wherein the at least some profiles further include information indicating a location visited by each user.
  15.   Receiving criteria that can be used to match a first user with one of the plurality of users is a current location of the first user and a location visited by at least one user of the plurality of users. The system according to claim 13, comprising obtaining information indicating a degree of proximity.
  16.   The network device further uses the first user's proximity to the other user when the current location of the first user is within a predetermined proximity of another user of the plurality of users. The system of claim 13, further configured to perform an action that includes determining a match.
  17.   The system of claim 13, wherein the network device is further configured to perform an action including transmitting a promotional item to the mobile device of the first user based on the current location of the first user. .
  18. The network device further includes:
    Automatically determining the location visited by the second user based on the location information transparently obtained from the mobile device of the second user;
    Further determining a match of one of the plurality of users using the determined location visited by the second user;
    The system of claim 13, wherein the system is configured to perform an action comprising:
  19. In a mobile device that manages location-based social networking,
    A data storage component for storing data and instructions;
    Execute the instructions,
    Determining a position of the mobile device, wherein the mobile device is associated with a first user;
    For each of a plurality of other mobile devices within a predetermined range of the mobile device, a user profile for each user associated with the mobile device within the range is received, each profile associating a plurality of characteristics with each user. And at least some of the characteristics include a level of credibility and a level of relevance, wherein the level of credibility is based on a plurality of behavior information associated with each user, Behavior information is obtained from a source other than each user, and the level of relevance is based on the behavior information obtained from behavior information of a certain sample size according to a threshold value ,
    Receiving criteria that can be used to match the first user to one of the users associated with at least one other mobile device within the predetermined range;
    Determining at least one match of the other users to the criteria based at least in part on the level of trustworthiness, the level of relevance, and the location of the first user;
    Providing a notification of a match to at least one of the first users or at least one of the other users;
    A processor configured to perform an action including:
    A mobile device comprising:
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